深度学习在甲状腺结节良恶性分类中的应用进展  

Application Progress of Deep Learning in the Classification of Benign and Malignant Thyroid Nodule

作　　者：张文凯 王晓燕[1] 刘静[1] 周启香 贺鑫 Zhang Wenkai;Wang Xiaoyan;Liu Jing;Zhou Qixiang;He Xin(College of Intelligence and Information Engineering,Shandong University of Traditional Chinese Medicine,Jinan 250355,Shandong,China)

机构地区：[1]山东中医药大学智能与信息工程学院,山东济南250355

出　　处：《激光与光电子学进展》2024年第8期27-38,共12页Laser & Optoelectronics Progress

基　　金：国家自然科学基金(82174528);山东省中医药科技项目(2021M146);山东省研究生教育质量提升计划(SDYKC19147)。

摘　　要：甲状腺结节是成人临床最常见的结节性病变之一,发病率一直居高不下。甲状腺结节有良性和恶性之分,后者即为甲状腺癌,会造成患者呼吸吞吐困难甚至危及患者生命。因此,识别甲状腺结节的良恶性是诊断和治疗甲状腺结节的首要问题。深度学习能够自动提取结节特征,并完成甲状腺结节的良恶性初步分类。随着深度学习分类准确率的不断提高,目前它已成为甲状腺结节良恶性辅助诊断的重要手段。为更好地进行甲状腺结节良恶性分类辅助诊断研究,对常用的结节分类性能评价指标进行介绍;按卷积神经网络、Transformer、深度神经网络、生成对抗网络、迁移学习、集成学习以及基于深度学习的计算机辅助诊断系统进行分类,对它们在甲状腺结节良恶性分类中的应用进行阐述,并进行综合对比分析;总结了目前研究中存在的问题,并对未来的研究方向进行了展望。Thyroid nodule is one of the most common clinical nodular lesions in adults,and its incidence rate is always high.Thyroid nodule can be classified into benign and malignant,and the latter is thyroid cancer,which can cause difficulties in breathing and swallowing,and even endanger the life of patients.Therefore,the identification of benign and malignant thyroid nodule is the primary problem in the diagnosis and treatment of thyroid nodule.Deep learning can automatically extract nodule features and complete the preliminary classification of benign and malignant thyroid nodule.With the continuous improvement of classification accuracy of deep learning,it has become an important means of auxiliary diagnosis of benign and malignant thyroid nodule.To better study the classification and auxiliary diagnosis of benign and malignant thyroid nodule,we introduce the commonly used indicators for the evaluation of nodule classification performance,and classify them according to the convolutional neural network,Transformer,deep neural network,generative adversarial network,transfer learning,ensemble learning,and computeraided diagnosis system based on deep learning,and elaborate their application in the classification of benign and malignant thyroid nodule.We conduct a comprehensive comparative analysis,summarize the existing problems in the current research,and provide prospects for future research directions.

关 键 词：甲状腺结节 良恶性分类 深度学习 图像处理 辅助诊断 

分 类 号：O436[机械工程—光学工程]